LEETCODE 199:LAST LEVEL PICK PATTERN: Efficient Solution for Binary Tree Right Side View

Welcome to another detailed walkthrough of a LeetCode problem! Today, we will dive into LeetCode Problem 199, "Binary Tree Right Side View." In this video, we will break down the problem, understand the requirements, explore various approaches, and finally, provide an efficient solution. Whether you're a beginner or an experienced coder, this video will help you understand and solve this problem effectively.
Problem Overview
LeetCode Problem 199, "Binary Tree Right Side View," requires us to return the values of the nodes that can be seen when the binary tree is viewed from the right side. This means, for each level of the tree, we need to identify the rightmost node. This problem tests our understanding of tree traversal and our ability to manipulate and access nodes in a specific order.
Requirements
The problem statement is as follows:
Given the root of a binary tree, imagine yourself standing on the right side of it and return the values of the nodes you can see ordered from top to bottom.
For example, given the following binary tree:
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Copy code
1
/ \
2 3
\ \
5 4
You should return [1, 3, 4].
Key Concepts
To solve this problem, we need to understand a few key concepts:
Tree Traversal: Traversing the tree to visit nodes in a particular order.
Level Order Traversal: Visiting nodes level by level.
Rightmost Node Identification: For each level, identifying the rightmost node.
Approach
There are multiple ways to approach this problem. The two most common methods are using Depth-First Search (DFS) and Breadth-First Search (BFS). Each has its own advantages, and we will explore both.
Depth-First Search (DFS)
In a DFS approach, we can use a recursive function to traverse the tree. We will start from the root and move to the rightmost node first. This ensures that the first node we encounter at each level is the rightmost one. We can use a list to keep track of the nodes at each level.
Breadth-First Search (BFS)
A BFS approach involves using a queue to traverse the tree level by level. For each level, we can add the rightmost node to our result list. This method ensures that we visit nodes in the exact order required by the problem statement.
Detailed Explanation
Depth-First Search (DFS) Approach
In the DFS approach, we perform the following steps:
Initialize a list to store the right side view.
Define a recursive function that traverses the tree.
For each node, check if it is the rightmost node of its level.
Add the node to the result list if it is the rightmost.
Recursively traverse the right subtree first, followed by the left subtree.
This approach ensures that the first node encountered at each level is added to the result list.
Breadth-First Search (BFS) Approach
In the BFS approach, we perform the following steps:
Initialize a queue and add the root node to it.
While the queue is not empty, process nodes level by level.
For each level, iterate through all nodes and keep track of the rightmost node.
Add the rightmost node to the result list.
Add the left and right children of each node to the queue for the next level.
This approach guarantees that we process nodes in the required order and correctly identify the rightmost node at each level.
Performance Analysis
The time complexity for both DFS and BFS approaches is O(N), where N is the number of nodes in the tree. This is because we visit each node exactly once. The space complexity for DFS is O(H), where H is the height of the tree, due to the recursion stack. For BFS, the space complexity is O(N) because we store nodes in a queue.
Practical Example
Let's consider a practical example to illustrate the BFS approach:
Given the binary tree:
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Copy code
1
/ \
2 3
/ \ \
4 5 6
\ \
7 8
We can see that the right side view of this tree is [1, 3, 6, 8]. We start by adding the root node (1) to the queue. At each level, we add the rightmost node (last node processed at that level) to our result list.
Summary
In this video, we covered the problem statement of LeetCode Problem 199, "Binary Tree Right Side View," and explored two common approaches to solve it: Depth-First Search (DFS) and Breadth-First Search (BFS). We discussed the key concepts, detailed steps, and performance analysis for both methods. By understanding and implementing these approaches, you will be well-equipped to tackle similar tree traversal problems.
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